Mobile devices like cellular phones are frequently used to search for local points of interest. The quality of the search result depends on the quality, freshness, and validity of the data available concerning those points of interest. Information concerning points of interest may be gathered in different ways. Conventionally, employees of the search provider may have roamed locations acquiring and inputting data about points of interest. Additionally, crowd-sourced data may also have been acquired. Unfortunately, crowd-sourced data may be inaccurate in a number of ways. Regardless of how the data was acquired, the freshness and continuing validity of the data controls the value of a search for a local point of interest. There may be nothing more fatal to a local search than directing a search user to a location that is no longer valid. Collecting information about relevant local destinations has been a challenge, particularly when the local destinations are highly transient and only semi-documented, if documented at all. Even if accurate relevant information can be acquired, a subsequent challenge concerns determining the ongoing validity of that information. Data that was initially valid may become invalid as a transient vendor moves, runs out of produce, or closes down for the day. Thus, a local search application may need to decide whether to initially provide and whether to continue to provide information about a point of interest.
Consider a city where a significant portion of the economy involves highly transient street vendors. The street vendors may be transient from season to season depending on what they sell (e.g., fresh fruit), may be transient from day to day depending on what they have available (e.g., fresh catch of the day), may be transient from time-of-day to time-of-day (e.g., hot dog vendor near office building at noon but near baseball stadium in evening), may be transient in their operating hours (e.g., only stay open while they have fresh fish) or may be transient for other reasons. These impromptu and semi-official destinations may be an integral part of the consumer landscape and thus relevant to local searches. Unfortunately, even if accurate, relevant, and valid information can be acquired about these types of points of interest, the information may have a very short lifespan due to the temporal and spatial transiency of the vendors.
Removing data that is no longer valid from a crowd-sourced database may be equally or even more important than getting useful data into the crowd-sourced database in the first place. A user of a local search application may experience a first level of frustration if their search for a transient vendor produces no results. However, the user may experience a second, much higher level of frustration if a local search results in a wild goose chase for a vendor that has already closed up shop for the day or moved on.
A point of interest that may be transient, either temporally or spatially, may be referred to as a hyperlocal point of interest (HPOI). Acquiring timely crowd-sourced content concerning an HPOI facilitates improving the quality of a local search. Removing stale information also facilitates improving the quality of a local search. Like it is for the fruit or fish vendor, freshness matters to crowd-sourced content concerning moving targets like HPOI. Unlike the fruit or fish vendor who has a constant incentive (e.g., sales) to insure their product is fresh, there may be little incentive for potential crowd-sourcers to provide information about HPOI. Additionally, even if a crowd-sourcer enters data about the current state of an HPOI, the crowd-sourcer may not be able to accurately predict or report on when the HPOI may become out-of-date.